In this paper, we consider dynamic channel allocation for remote state estimation of
multiagent systems. For each subsystem, a sensor measures its state and transmits the data …

In this article, we consider the problem of remote state estimation of a Gauss–Markov
process, where a sensor can, at each discrete time instant, transmit on one out of M different …

This paper considers optimal attack attention allocation on remote state estimation in multi-
systems. Suppose there are M independent systems, each of which has a remote sensor …

This paper investigates the multi-channel transmission scheduling problem for remote state
estimation based on a hopping scheme in cyber-physical systems. The smart sensor sends …

This article presents a learning-based algorithm for solving the online source-seeking
problem with a multiagent system under an unknown dynamical environment. Our algorithm …

In this paper, we study a sampling and transmission scheduling problem for multi-source
remote estimation, where a scheduler determines when to take samples from multiple …

We define and analyze a multi-agent multi-armed bandit problem in which decision-making
agents can observe the choices and rewards of their neighbors under a linear observation …

In this paper, we consider a class of restless multiarmed bandit processes (RMABs) that
arises in dynamic multichannel access, user/server scheduling, and optimal activation in …

We investigate a remote estimation problem in which a transmitter observes a Markov
source and chooses the power level to transmit it over a time-varying packet-drop channel …

In this paper, we study the remote estimation problem of a Markov process over a channel
with a cost. We formulate this problem as an infinite horizon optimization problem with two …